Data Engineer

BOYLE Sports; Dundalk; Hybrid; GBP 70,000 - 110,000; Full time

Job summary

BOYLE Sports is seeking a Data Engineer to design, build, and maintain scalable data pipelines in a cloud-based environment. You will work with batch and real-time ELT processes, primarily on AWS, to support analytics for customer acquisition, operations, and sports betting insights.

The role requires collaboration with data architects, product teams, analysts, and IT, delivering robust data infrastructure using S3, Glue, Lambda, and Redshift, plus Airflow/MWAA orchestration.

Qualifications

• Minimum 3 years of professional experience in data engineering or related tech role.
• Hands-on experience with cloud data platforms, especially AWS.
• Experience with large-scale production databases and SQL-based data warehouses (Redshift/Snowflake/BigQuery).
• Proven track record building ELT pipelines with dbt, Airflow, and Python.
• Familiarity with big data and streaming tech (Kafka, Spark).
• Experience with containers and orchestration (Docker, Kubernetes).

Responsibilities

• Design, build, and maintain scalable batch and real-time data pipelines.
• Develop ELT workflows to extract, transform, and load large datasets from multiple sources.
• Develop and maintain cloud-based data infrastructure using AWS services (S3, Glue, Lambda, Redshift).
• Implement orchestration and scheduling via Airflow or MWAA.
• Collaborate with data architects, analysts, and stakeholders from project inception to delivery.
• Ensure reliability, performance, and scalability of data pipelines and platforms.

Skills

SQL

Python

Airflow

dbt

AWS

Data Modeling

Kafka

Spark

Redshift

Snowflake

Docker

Kubernetes

Education

Bachelor's degree in a technical field

Tools

Amazon Redshift

Snowflake

Google BigQuery

dbt

Apache Airflow

AWS Glue

AWS Lambda

S3

Kubernetes

Docker

Kafka

Spark

Job description

Location: United Kingdom Remote, Ireland Remote, Gibraltar Hybrid

The Role:

The Data Engineer is responsible for designing, building, and maintaining scalable data pipelines and data platforms that support both batch (ELT) and real-time data processing. The role ensures reliable and efficient extraction, transformation, and loading of data from a wide range of internal and external sources to support business intelligence and analytics.

Working within a cloud-based data environment built primarily on Amazon Web Services, the Data Engineer will develop and maintain data infrastructure that enables the organization to make data-driven decisions. The solutions delivered will support analytical insights across the business, particularly in areas such as customer acquisition, operational performance, and analytics related to sports betting activities.

The role requires close collaboration with data architects, product teams, analysts, IT teams, and business stakeholders from project inception through to delivery.

• Design, develop, and maintain scalable batch and real-time data pipelines.
• Build ELT workflows to extract, transform, and load large datasets from multiple internal and external sources.
• Develop and maintain cloud-based data infrastructure using services such as Amazon S3, AWS Glue, AWS Lambda, and Amazon Redshift.
• Implement orchestration and scheduling workflows using Apache Airflow or Amazon MWAA.
• Develop data transformations and modelling processes using SQL and dbt.
• Integrate streaming and large-scale processing solutions using technologies such as Apache Kafka and Apache Spark.
• Ensure the reliability, performance, and scalability of production data pipelines and infrastructure.
• Participate in a scheduled on-call rotation to monitor, troubleshoot, and resolve high-priority data pipeline issues, ensuring the reliability of the data platform during weekends and bank holidays.
• Support the integration of data into enterprise data warehouses such as Snowflake or Redshift.

Security, Compliance & Governance:

• Implement secure data handling practices within cloud-based data platforms.
• Support the management of data access, permissions, and role-based controls across data systems.
• Ensure data pipelines and storage systems comply with internal governance policies and regulatory requirements.
• Maintain high standards of data quality, integrity, and traceability.
• Contribute to the implementation of data governance frameworks and best practices.
• Collaborate with data architects to design and evolve scalable data architecture.
• Work closely with product teams, analysts, and business stakeholders to translate business requirements into technical data solutions.
• Partner with IT and infrastructure teams to support system integration and platform stability.
• Participate in agile development practices including sprint planning, reviews, and technical discussions.
• Communicate effectively with both technical and non-technical stakeholders.
• Identify and implement opportunities to automate manual data processes.
• Continuously improve pipeline reliability, monitoring, and operational efficiency.
• Redesign and optimize data infrastructure to support increasing data volumes and evolving business requirements.
• Evaluate and introduce new tools, technologies, and best practices to enhance the data platform.
• Promote a culture of innovation and continuous improvement within the data engineering team.

The Person – Experience:

• Minimum of 3 years’ professional experience in data engineering or a related technical role.
• Hands-on experience working with cloud data platforms, particularly Amazon Web Services.
• Strong experience working with large-scale production databases and SQL-based data warehouses such as Amazon Redshift, Snowflake, or Google BigQuery.
• Proven experience developing ELT pipelines using dbt, Apache Airflow, and Python.
• Familiarity with big data and streaming technologies such as Apache NiFi, Apache Kafka, and Apache Spark.
• Experience with containerization and orchestration technologies including Docker and Kubernetes.

Skills & Attributes:

• Strong SQL and data modelling capabilities.
• Proficiency in Python for data pipeline development.
• Strong analytical and problem-solving skills.
• Ability to work with complex and large-scale datasets in production environments.
• A proactive and innovative mindset with a focus on continuous improvement.
• Ability to adapt quickly in a fast-paced and evolving technical environment.
• Strong communication and collaboration skills.
• Excellent English communication skills with ability to convey complex technical concepts to international teams.
• Willingness to contribute ideas, share knowledge, and participate in technical discussions.

Company:

BOYLE Sports is an international sports betting and gaming company, with an extensive online business and retail portfolio. Founded by John Boyle in 1982, the Irish family-owned firm has grown to become Ireland’s largest and most successful independently-owned bookmaker and has over 390 shops across Ireland and the UK. Its Head Office is located on the outskirts of Dundalk in the Republic of Ireland and the company currently employs over 2,700 employees across Ireland, the UK and Gibraltar. BOYLE Sports offers a world class betting and gaming experience with a ‘Customer First’ approach, committed to bringing customers closer to the action. Its mission is boosted by a rich sponsorship portfolio – the company is a proud principal sponsor of West Ham United Football Club and it stays at the heart of the action all year round by backing some of sport’s most prestigious events, including the Irish Grand National, the Irish Greyhound Derby and the World Grand Prix of Darts.